Ensure the system tracks performance and handles data drift.
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Select appropriate algorithms (supervised, unsupervised, or deep learning). Ensure the system tracks performance and handles data drift
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Establish metrics (accuracy, F1-score) and handle hyperparameter tuning.
Plan the deployment, focusing on real-time vs. batch inference.
Clarify requirements, business goals, and constraints (e.g., latency, throughput).